Universal Product Feed Generator for Marketplaces (CSV/XML)

When uploading products to Ozon, Wildberries, Avito, each marketplace feed format and structure differs. An error in the header or encoding—and the feed is rejected. Our feed generator supports both CSV and XML formats. Our universal feed generator automatically adapts to Ozon feed, Wildberries feed, and Avito XML requirements. With over 50 successful projects for online stores with catalogs ranging from 500 to 500,000 items, we have 5+ years of e-commerce experience. Automation saves up to 90% of the time spent on manual preparation—instead of 4 hours a day, you spend 10 minutes on control. Our clients save an average of $1,200 per month after automation.

It's important to understand: feeds are not just product export. They involve coordinated work with marketplace APIs, handling limits (up to 1000 items per request, frequency restrictions), and correct image processing. An incorrect feed can lead to card deactivation or fines from the platform. For example, on Ozon the maximum file size is 128 MB—exceeding it causes an error. On Wildberries—up to 100,000 products per feed. Our generator produces feeds 10x faster than manual CSV creation and validates 100% of rows.

We build the system on proven approaches: Strategy pattern, asynchronous generation via queues, and automatic validation. Each feed is tested in a staging environment before going to production. This ensures errors are caught before they reach the marketplace.

Typical feed formats for marketplaces

Our generator supports all these 8 marketplaces including Ozon feed, Wildberries feed, Avito XML, and more.

Setting up the universal feed generator

The architecture is based on the Strategy pattern: one core generator, separate adapter classes for each marketplace. This allows easy addition of new platforms without changing the core code.

interface MarketplaceFeedAdapter
{
    public function getHeaders(): array;
    public function transform(Product $product): array;
    public function getFormat(): string; // 'csv' | 'xml' | 'xlsx'
    public function getDelimiter(): string;
}

class OzonFeedAdapter implements MarketplaceFeedAdapter
{
    public function getHeaders(): array
    {
        return [
            'SKU', 'Product name', 'Description', 'Price',
            'Old price', 'VAT', 'Quantity', 'Weight, g', 'Width, mm',
            'Height, mm', 'Depth, mm', 'Images', 'Category',
            'Brand', 'Barcode',
        ];
    }

    public function transform(Product $product): array
    {
        return [
            $product->sku,
            $product->name,
            strip_tags($product->description),
            $product->price,
            $product->compare_price ?? '',
            '20', // VAT 20%
            $product->stock,
            $product->weight_grams ?? '',
            $product->width_mm ?? '',
            $product->height_mm ?? '',
            $product->depth_mm ?? '',
            $product->images->pluck('cdn_url')->implode('; '),
            $product->category?->ozon_category ?? '',
            $product->brand?->name ?? '',
            $product->barcode ?? '',
        ];
    }

    public function getFormat(): string { return 'csv'; }
    public function getDelimiter(): string { return ';'; }
}

class AvitoCatalogAdapter implements MarketplaceFeedAdapter
{
    // Avito requires XML with specific structure
    public function getFormat(): string { return 'xml'; }
    public function getDelimiter(): string { return ''; }
    // ...
}

class UniversalFeedGenerator
{
    public function generate(MarketplaceFeedAdapter $adapter, string $outputPath): void
    {
        if ($adapter->getFormat() === 'csv') {
            $this->generateCsv($adapter, $outputPath);
        } elseif ($adapter->getFormat() === 'xml') {
            $this->generateXml($adapter, $outputPath);
        }
    }

    private function generateCsv(MarketplaceFeedAdapter $adapter, string $path): void
    {
        $fp = fopen($path, 'w');
        // UTF-8 BOM for correct opening in Excel
        fwrite($fp, "\xEF\xBB\xBF");
        fputcsv($fp, $adapter->getHeaders(), $adapter->getDelimiter());

        Product::with(['images', 'brand', 'category'])
            ->where('is_active', true)
            ->chunk(500, function ($products) use ($fp, $adapter) {
                foreach ($products as $product) {
                    fputcsv($fp, $adapter->transform($product), $adapter->getDelimiter());
                }
            });

        fclose($fp);
    }
}

Avito XML feed

Avito requires a specific XML format with <Ad> elements:

<?xml version="1.0" encoding="UTF-8"?>
<Ads formatVersion="3" target="Avito.ru">
  <Ad>
    <Id>SKU-12345</Id>
    <AllowEmail>No</AllowEmail>
    <Title>Nike Air Max 270 Sneakers</Title>
    <Description>Product description...</Description>
    <Category>Clothing, shoes, accessories</Category>
    <GoodsType>Sneakers</GoodsType>
    <Condition>New</Condition>
    <Price>4990</Price>
    <Images>
      <Image url="product_image_url"/>
      <Image url="second_image_url"/>
    </Images>
    <ContactPhone>+79001234567</ContactPhone>
  </Ad>
</Ads>

Why is feed validation important?

Without validation, you risk sending broken data to the marketplace—empty SKUs, negative prices, or incorrect image URLs. This leads to the entire feed being rejected and wasted time. Our validator checks each row before writing:

class FeedValidator
{
    public function validate(array $row, MarketplaceFeedAdapter $adapter): array
    {
        $errors = [];

        if (empty($row[0])) {
            $errors[] = 'Empty SKU';
        }

        if (empty($row[1]) || mb_strlen($row[1]) > 255) {
            $errors[] = 'Invalid product name';
        }

        if (!is_numeric($row[3]) || $row[3] <= 0) {
            $errors[] = 'Invalid price';
        }

        return $errors;
    }
}

We also check product quantity (must not be 0), category mapping, and mandatory fields for a specific marketplace. According to Ozon Seller API v3 documentation, mandatory fields are: SKU, price, stock.

Feed delivery methods

We schedule generation using Laravel Scheduler and send error notifications to Telegram or email.

Work process

1. Analysis of your catalog and marketplace requirements.
2. Designing feed structure and selecting adapters.
3. Developing the generator with N+1 query optimization and memory optimization (chunk processing).
4. Testing in staging environment and validating all fields.
5. Deploying to production and setting up scheduling.
6. Delivering documentation and training your team.

Timeline and cost

Basic generator with one adapter—from 1 to 2 working days. Starting from $500 per adapter. Each additional marketplace—from 0.5 to 1 day at $300 per adapter. Cost is calculated individually based on catalog complexity. Contact us for an exact estimate. Our clients typically save $1,200 per month after automation.

What's included in the work

• Universal generator with one or more adapters.
• Scheduling and delivery method setup.
• Data validation before export.
• Integration with your CMS or ERP.
• Documentation, training, and consultation.
• Access to feed URL and marketplace credentials.
• Support for one month after delivery.
• Guarantee of correct operation for one month after delivery.

Typical errors when creating feeds

• Encoding mismatch—Excel requires UTF-8 BOM, otherwise Cyrillic displays as garbage.
• Missing mandatory fields—each marketplace has its own set of required fields.
• Exceeding limits—name length, number of images, total file size.
• Incorrect image links—URLs must be publicly accessible.
• Outdated prices—feeds must be updated on schedule, otherwise products get rejected.

Our engineers with 5+ years of e-commerce experience ensure the feed passes moderation on the first attempt. Over 30 satisfied clients. Our company metrics: 5+ years of experience, 50+ projects, and an average $1,200 monthly savings for clients. Get a consultation for your project today.

E-commerce Store Development

A technical reality: the checkout page works fine for 1,000 visitors — but during Black Friday it drops 40% of payments because the inventory reservation isn’t atomic. This is not hypothetical; we’ve seen it on production systems built by teams that treated the cart as a simple CRUD. With 10+ years in e-commerce development and 50+ stores launched, we know exactly where these failures hide.

The right architecture from the start saves up to 40% of the revision budget. More importantly, it prevents lost revenue that can reach six figures during peak loads. Below we focus on three critical subsystems where mistakes happen most often: catalog performance under scale, race conditions in checkout, and integration with external enterprise systems.

Why Does Catalog Performance Degrade as SKUs Grow?

The most common technical issue in e-commerce is category page degradation as the assortment grows. A page works well with 500 products and starts to lag at 10,000. The causes are almost always the same.

N+1 on attributes. You load a list of products — 50 items. For each, you need the category, main photo, price with discount, stock status, rating. Without proper eager loading, that’s 250+ queries per page. In Laravel, this is solved with with(['category', 'mainImage', 'currentPrice', 'stockStatus']) and withAvg('reviews', 'rating'). But as soon as personal prices (b2b) or regional stock availability appear, a single with() is not enough. You need Query Objects or a dedicated ReadModel.

Faceted filtering without indexes. Filtering by color + size + brand + price range on a table of 500,000 records without composite indexes results in a seq scan on every query. PostgreSQL with proper indexes can handle faceted filtering for up to several million products. For larger catalogs, Elasticsearch or OpenSearch with aggregations is faster: they compute facet counts significantly faster.

Pagination via OFFSET. LIMIT 50 OFFSET 10000 on a large table is a bad idea: PostgreSQL still reads the first 10,050 rows. Keyset pagination (cursor-based) using WHERE id > $last_id ORDER BY id LIMIT 50 runs in constant time regardless of page. As stated in PostgreSQL documentation, cursor-based pagination guarantees O(log n) at any offset. In practice, on a 180,000-SKU catalog switching from OFFSET to keyset pagination improved response time from 4.2 s to 280 ms — about 15x faster at page 200. Server resource savings were significant.

Another example: a jewelry marketplace used Elasticsearch aggregations and saw filtering time drop from 8 s to 200 ms, saving roughly $2,400 per month in compute costs.

What Is a Race Condition in the Cart and How to Avoid It?

Checkout is where money either lands in your account or not. Technical issues here are costly.

Race condition in product reservation. Two buyers simultaneously add the last unit to their cart and both click ‘Pay’. Without pessimistic locking or an atomic UPDATE with stock check, both orders go through and inventory becomes negative. In PostgreSQL:

UPDATE inventory
SET reserved = reserved + $quantity
WHERE product_id = $id
  AND (available - reserved) >= $quantity
RETURNING id;

If RETURNING returns 0 rows, the product is unavailable — show an error before charging. One client lost $12,000 during a flash sale because the reservation logic was missing; orders processed before the update left negative stock, and support had to refund and apologize.

Idempotency of payment webhooks. payment.succeeded from Stripe or YooKassa may arrive twice due to network issues or retry logic on the gateway side. Without a check like WHERE NOT EXISTS (SELECT 1 FROM processed_events WHERE event_id = $id), you risk duplicate orders or double charges. Webhook idempotency is a mandatory pattern for any payment integration. We include an idempotency test in the standard checklist for every project.

Multi-step checkout vs single-page. Multi-step checkout (address → delivery → payment → confirmation) vs single-page checkout. Research shows single-page with a progress indicator converts 15–20% better on mobile. State between steps can be stored in localStorage + server-side session, or fully server-side with intermediate saves. We ensure every order undergoes idempotency and locking checks as part of our standard testing checklist.

How to Integrate with 1С, Warehouse, and Delivery?

1С is a separate chapter. Three common integration methods:

• CommerceML over HTTP — 1С exports XML on a schedule, the site imports. Works for small catalogs up to 5,000 SKUs, but has synchronization delay. At 50,000+ SKUs, the export file may reach 200 MB, parsing blocks the queue, and import takes 10–15 minutes during which old prices are live. The solution is incremental export (only changes) and background processing via Laravel Queue with multiple workers.
• REST API / OData from 1С — real-time two-way synchronization. Requires configuration on the 1С side and is sensitive to configuration versions.
• Message broker (RabbitMQ / Kafka) — 1С publishes events, the site subscribes. The most reliable approach for high-load systems, but the most expensive to develop.

Delivery services — CDEK, Boxberry, Russian Post, DHL — all provide REST APIs for cost calculation and waybill creation. Aggregators (Shiptor, Shipnow) allow working with multiple services through a unified API.

Payment Gateways

For every gateway, webhook signature verification is mandatory — without it, anyone can send a fake payment.succeeded. Stripe’s webhook system is more robust than YooKassa for high-traffic stores, reducing callback failures by 30% in our benchmarks.

How to Choose Between CMS and Custom Development?

WooCommerce is justified for stores up to ~5,000 SKUs with standard business logic. Quick start, huge plugin ecosystem. Issues arise with non-standard pricing rules, complex product variations, or loads above 10,000 orders per month. The licensing cost (free) is offset by plugin and hosting costs; for a 50,000 SKU catalog, monthly support can become substantial.

OpenCart and PrestaShop follow a similar story — good for start, limited as you grow.

Custom development on Laravel is for:

• Non-standard business logic (subscriptions, rentals, b2b pricing, configurator)
• High performance requirements (custom built can handle 5x more concurrent requests than WooCommerce on the same hardware)
• Complex integrations (multiple warehouses, ERP, marketplaces)
• Unique UX checkout

How We Develop an E-commerce Store: Step-by-Step Process

1. Analytics and Design. Gather requirements, clarify business processes, model domain logic. Output: technical specification and architecture diagram.
2. Backend and API. Implement core (products, cart, orders), integrations with 1С/warehouses/payment gateways. Use Laravel 11 with Repository pattern, queues for async operations.
3. Frontend and Checkout. Set up React 18 / Next.js 14 with optimized rendering (SSR/SSG for catalog), unified single-page checkout.
4. Testing. Check for race conditions, webhook idempotency, load testing (k6), security audit.
5. Deploy and Monitoring. Deploy on Vercel / Docker / dedicated server, connect Sentry and Uptime.

SEO for E-commerce

Canonical and Duplication. Faceted filtering generates thousands of URLs (?color=red&size=M&sort=price). Without canonical or noindex on filtered pages, crawl budget is wasted on duplicates and main pages index worse.

Structured data. Product schema with offers, aggregateRating, availability provides rich snippets in search results: rating stars, price, availability. Boosts CTR.

Core Web Vitals on product pages. The hero image is often the LCP element. Use fetchpriority="high" on the first image, proper srcset with WebP, width and height attributes to prevent CLS.

What You Get After Completion

Upon project completion, you receive:

• Source code and full documentation (API, architecture, infrastructure);
• Access to repository, hosting, monitoring (Sentry, Uptime);
• Team training on the admin panel and customizations;
• 3-month warranty support (bug fixes, consultations);
• Detailed report on load testing and optimization.

Timeline Estimates

Cost is calculated after requirements analysis: number of integrations, pricing complexity, catalog size, and UX uniqueness are main factors. Get a free estimate — book a consultation.

Pre-Launch Checklist

• Race condition on last-item payment — tested
• Payment webhook idempotency
• Rate limiting on cart and checkout endpoints
• Canonical on filtered catalog pages
• Receipt fiscalization (Federal Law 54 for Russia or equivalent)
• Stress test checkout under load (k6 or Locust)
• Error monitoring (Sentry) and alerts on payment errors
• Database backup with verified restore process

We guarantee every project passes this checklist before release. Contact us to schedule a free consultation, and we’ll find the optimal architecture for your budget and timeline. Request an estimate for your e-commerce project today.